Research Design,ODK Mobile Data Collection,GIS Mapping,Data Analysis using NVIVO and PYTHON Course

Research Design,ODK Mobile Data Collection,GIS Mapping,Data Analysis using NVIVO and PYTHON Course


Welcome to the Research Design, ODK Mobile Data Collection, GIS Mapping, and Data Analysis using NVivo and Python course! In today's research landscape, incorporating diverse methodologies and tools is essential for conducting comprehensive and impactful studies. This course is meticulously crafted to equip participants with a versatile skill set spanning research design principles, mobile data collection using ODK, GIS mapping for spatial analysis, and data analysis utilizing NVivo and Python. Whether you're an academic, researcher, or practitioner, mastering these methodologies and tools will empower you to design and execute research projects with precision and depth, ensuring robust findings and informed decision-making.

Course Objectives:

  1. Research Design Proficiency: Develop a thorough understanding of research design principles, including conceptualization, operationalization, and hypothesis formulation, to lay the groundwork for conducting methodologically sound research studies.
  2. ODK Mobile Data Collection Mastery: Acquire the skills to design, implement, and manage data collection processes using ODK, a versatile tool for mobile data collection, enabling seamless data collection in both online and offline environments.
  3. GIS Mapping Techniques: Gain expertise in GIS mapping techniques, including data visualization, spatial querying, and spatial analysis, to uncover spatial patterns and relationships in research data using geographic information systems.
  4. Qualitative Data Analysis with NVivo: Explore qualitative data analysis methodologies using NVivo, delving into coding, thematic analysis, and visualization techniques to derive meaningful insights from qualitative data sources.
  5. Quantitative Data Analysis with Python: Master quantitative data analysis techniques using Python programming language, covering data manipulation, statistical analysis, and visualization to analyze and interpret quantitative research data effectively.

Organization Benefits:

  1. Enhanced Research Capacities: Equipping employees with a comprehensive skill set spanning research design, data collection, GIS mapping, and data analysis enhances the organization's research capacities, facilitating the conduct of rigorous and impactful research studies.
  2. Improved Efficiency and Productivity: Leveraging tools such as ODK for mobile data collection and Python for quantitative analysis streamlines research processes, leading to increased efficiency, productivity, and reproducibility in research workflows.
  3. Enhanced Data Quality and Rigor: Utilizing ODK for mobile data collection ensures data accuracy and integrity, while GIS mapping enables spatial visualization and analysis, enhancing the rigor and reliability of research findings.
  4. Facilitated Collaboration and Knowledge Sharing: Integration of diverse research methodologies and tools fosters collaboration and knowledge sharing among research teams, enabling seamless data exchange, analysis, and interpretation across projects.
  5. Informed Decision-Making and Strategic Planning: The ability to collect, analyze, and interpret both qualitative and quantitative data using ODK, GIS, NVivo, and Python empowers organizations to make evidence-based decisions and develop informed strategies and policies.

Target Participants:

 This course is ideal for researchers, academics, professionals, and students seeking to enhance their research skills and methodologies across various domains. Target participants include social scientists, environmental researchers, public health professionals, urban planners, and individuals from diverse disciplinary backgrounds interested in conducting rigorous and impactful research studies employing a multidimensional approach.

Course Outline:

  1. Introduction to Research Design Principles
    • Understanding research paradigms and approaches
    • Conceptualization, operationalization, and hypothesis development
    • Case Study: Designing a research study on community engagement initiatives
  2. ODK Mobile Data Collection Techniques
    • Introduction to ODK and its features for mobile data collection
    • Designing data collection forms and surveys
    • Implementing data collection protocols in ODK
    • Case Study: Conducting a field survey on healthcare access using ODK
  3. GIS Mapping Fundamentals
    • Overview of GIS mapping concepts and applications
    • Spatial data visualization and interpretation
    • Spatial querying and analysis techniques
    • Case Study: Mapping environmental pollution hotspots using GIS mapping tools
  4. Qualitative Data Analysis with NVivo
    • Introduction to NVivo software for qualitative data analysis
    • Importing and coding qualitative data in NVivo
    • Thematic analysis and visualization techniques
    • Case Study: Analyzing focus group discussions on community development using NVivo
  5. Quantitative Data Analysis with Python
    • Introduction to Python programming language for data analysis
    • Data manipulation and cleaning in Python
    • Statistical analysis and visualization using Python libraries (e.g., Pandas, Matplotlib)
    • Case Study: Analyzing survey data on consumer preferences using Python
  6. Advanced Analysis Techniques in NVivo
    • Advanced coding methodologies and strategies
    • Inter-rater reliability assessment
    • Visualization techniques for qualitative data
    • Case Study: Conducting a content analysis of interviews using advanced NVivo features
  7. Advanced Analysis Techniques in Python
    • Inferential statistics (e.g., t-tests, ANOVA) using Python libraries (e.g., SciPy)
    • Machine learning algorithms for predictive modeling using Python libraries (e.g., Scikit-learn)
    • Interpretation and reporting of quantitative analysis results
    • Case Study: Predicting customer churn using machine learning algorithms in Python
  8. Mixed-Methods Research Design
    • Overview of mixed-methods research designs and applications
    • Integrating qualitative and quantitative data collection and analysis
    • Triangulation and data convergence strategies
    • Case Study: Designing a mixed-methods study on healthcare access and utilization
  9. Data Integration and Synthesis
    • Integrating data from multiple sources (e.g., ODK, GIS, NVivo, Python)
    • Synthesizing qualitative and quantitative findings
    • Drawing conclusions and implications from integrated data
    • Case Study: Integrating data on urban mobility patterns to inform transportation planning
  10. Ethical Considerations in Research
    • Ethical principles in research and human subjects protection
    • Ethical considerations in data collection, analysis, and reporting
    • Case Study: Addressing ethical challenges in research on vulnerable populations
  11. Research Dissemination and Impact
    • Strategies for disseminating research findings to diverse audiences
    • Communicating research findings effectively through various channels
    • Measuring research impact and engagement
    • Case Study: Developing a research dissemination plan for a public health intervention study
  12. Project Management and Collaboration
    • Project planning, organization, and management best practices
    • Collaboration tools and platforms for research teams
    • Case Study: Managing a collaborative research project on sustainable development
  13. Research Proposal Development
    • Components of a research proposal (e.g., background, objectives, methodology)
    • Writing effective research proposals for funding applications
    • Case Study: Developing a research proposal for a grant submission in environmental conservation


Essential Information


  1. Our courses are customizable to suit the specific needs of participants.
  2. Participants are required to have proficiency in the English language.
  3. Our training sessions feature comprehensive guidance through presentations, practical exercises, web-based tutorials, and collaborative group activities. Our facilitators boast extensive expertise, each with over a decade of experience.
  4. Upon fulfilling the training requirements, participants will receive a prestigious Global King Project Management certificate.
  5. Training sessions are conducted at various Global King Project Management Centers, including locations in Nairobi, Mombasa, Kigali, Dubai, Lagos, and others.
  6. Organizations sending more than two participants from the same entity are eligible for a generous 20% discount.
  7. The duration of our courses is adaptable, and the curriculum can be adjusted to accommodate any number of days.
  8. To ensure seamless preparation, payment is expected before the commencement of training, facilitated through the Global King Project Management account.
  9. For inquiries, reach out to us via email at [email protected] or by phone at +254 114 830 889.
  10. Additional amenities such as tablets and laptops are available upon request for an extra fee. The course fee for onsite training covers facilitation, training materials, two coffee breaks, a buffet lunch, and a certificate of successful completion. Participants are responsible for arranging and covering their travel expenses, including airport transfers, visa applications, dinners, health insurance, and any other personal expenses.

Course Date Duration Location Registration
08/07/2024 To 19/07/2024 10 Days Nairobi Kenya
05/08/2024 To 16/08/2024 10 Days Dubai, UAE
02/09/2024 To 13/09/2024 10 Days Nairobi Kenya
30/09/2024 To 11/10/2024 10 Days Nairobi Kenya
25/11/2024 To 06/12/2024 10 Days Nanyuki, Kenya
23/12/2024 To 03/01/2025 10 Days Nairobi Kenya